Maramara me te Iwi Taketake: Data and the Indigenous Group
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PETER CLEAVE Maramara me te Iwi Taketake: Data and the Indigenous Group Abstract This paper considers Indigenous groups and data. The paper begins with fifteen assorted questions which are addressed in various ways in the next two sections. The second section is a review of ‘Indigenous Data Sovereignty’ a collection by Kukutai and Taylor of 2016. This collection is seen as an excellent statement of the position of the Indigenous group regarding data and each chapter is reviewed in several paragraphs. Beginning with Kukutai and Taylor, the third and final section is a commentary on recent literature on data with reference to the Nation-state, Big Tech and Indigenous groups. This section considers a shifting situation involving machine learning and the hunting, gathering and farming of data. A reappraisal of the way data is used in the context of the Indigenous group, the Nation state and Big Tech Professor Peter Cleave is a Research Associate in the Faculty of Health and Environmental Sciences (AUT University), a Visiting Fellow in Te Ara Poutama (AUT University), a Member of Common Room, Wolfson College (Oxford University), and a Broadcaster in Te Reo Maori at Kia Ora FM
2 Maramara me te Iwi Taketake
is proposed. That reappraisal involves new
considerations of identity in forms of ethnicity,
nationalism and tribalism as well as the way
Indigenous groups are defined by others and the
ways in which they define themselves.
Assorted questions
1. How does data define the ethnic group?
2. Who owns what data about whom? Why?
3. Data feeds profiles?
4. Data is a mirror?
5. Data is resource?
6. Data is money?
7. In data we trust?
8. Data feeds the future?
9. Data is identity?
10. Does Machine Learning throw up a field of
data that imprisons the imagination?
11. Do data and Machine Learning provide a
field of dreams?
12. What are the critical criteria for data
collection by Indigenous groups, Nation-
states or Big Tech?
13. We are known by our data?
14. Does data define the Nation-state?
15. Data is power?
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 3
Review of Indigenous Data Sovereignty,
Towards an Agenda (Kukutai & Taylor, 2016)
Before colonisation data was controlled from within
Indigenous groups and not from without. After
colonisation and in a variety of ways Indigenous
peoples came to be dominated by nation states. One
of those ways was the taking control of the
assemblage of data, its processes of collection, the
way it was and is structured, its storage and its use.
Kukutai and Taylor as Editors and all contributors
to the collection that is Indigenous Data Sovereignty,
Towards an Agenda comment on data control in
various ways.
Indigenous Data Sovereignty opens with an
Introduction by Kukutai and Taylor entitled Data
Sovereignty for Indigenous Peoples: current practices
and future needs. For anyone interested in that kind
of a thing there is a several page list of acronyms at
the outset of the book and this is good because there
is a bewildering amount. After this and a useful
Preface the Introduction begins with reference to the
CANZUS conference in Canberra in 2015. The idea
was to ‘identify and develop an indigenous data
sovereignty agenda, leveraging international
instruments such as the United Nations Declaration
on the Rights of Indigenous Peoples (UNDRIP).’
Kukutai and Taylor make the claim which seems
accurate that this is the first book to ‘engage with
the topic of data sovereignty from an Indigenous
standpoint.’
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The thrust of the collection is to shift from ‘servicing
government requirements’ to support ‘indigenous
peoples’ development agendas’, to shift from a
development-policy nexus in nation-state settings
and to reflect on how the statistical portrayal of
Indigenous peoples might be transformed. Various
points about census taking are considered to
emphasise this thrust.
Kukutai and Taylor note that in the present
situation for indigenous peoples around the world
there is a tendency to generate ‘crude social binaries
(indigenous-non indigenous) as input to public
policy’. They conclude the early part of their paper
saying, ‘…while not denying some role for
centralised data collection, what indigenous peoples
are seeking is a right to identity and meaningful
participation in decisions affecting the collection,
dissemination and stewardship of all data that are
collected about them.’
The above might be taken as the central premise in
the collection.
Megan Davis in Chapter Two introduces the topic of
the ‘Indigenous Navigator’ project, a way of reporting
on the implementation of Indigenous rights in
development and other matters. Her paper is
entitled ‘Data and the United Nations Declaration on
the Rights of Indigenous Peoples’. Davis starts by
stating the invisibility of indigenous people in data
collection of national statistics. Citing Stewart-
Harawira (2005) and others Megan Davis asks
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whether this is ‘to avoid considerations of
indigenous peoples’ right to self determination’ and
goes on to set out questions relevant to data
sovereignty. Davis points out logistical challenges
and gaps in the case of data collected about
indigenous peoples and mentions the fact that many
Indigenous peoples work in informal economies so
data collection is difficult in such areas. She asks
how data might be dis-aggregated so that
indigenous data might be more clearly seen. Davis
mentions the ‘indigenous identifier’ used in some
Latin American studies.
Davis then discusses UNDRIP and data suggesting
that it provides ‘the common framework of the
normative content of the rights of indigenous
peoples and is therefore important to understanding
the issues of indigenous data sovereignty’. There is
then a good discussion of UNDRIP followed by a
consideration of how to measure the
implementation of the human rights standards that
it affirms be this by ‘fact based’, objective or
‘judgement based’ subjective methods. Davis
concludes with a discussion of the Indigenous
Navigator project now found in several UN
organisations.
Mathew Snipp in the next chapter examines the
concept of ‘data sovereignty’ and asks how
indigenous people might claim and gain greater
control over data related to them including
determining access to that data. As Snipp mentions
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at the outset, data sovereignty ‘is a uniquely twenty-
first-century expression that arises directly from the
explosive growth of information associated with the
internet and the spread of mobile phone technology’.
Regarding the role of the Nation-state in all this he
gives the example of Google leaving China to be
replaced by Baidu.
Snipp asks from whom might data be obtained and
talks about the way indigeneity might be defined
and offers 1492 as a benchmark in the Western
Hemisphere defined in various ways by different
nation states. In Mexico speaking an Indigenous
language is a key indicator. Various points are made
about defining tribes and recognising them in the
USA including the idea of blood quantum.
Some people report that they are American Indians
but do not state a tribe (20%). This makes it difficult
for tribes to assess data on their members. They do
not have the means to do this.
Then there is the question as to where people reside,
many living across cities rather than in discrete
areas.
Snipp goes on to ask what is data about and what
is it for? Surveillance by a settler state or to assess
the specific needs of the indigenous community? He
suggests that African Americans, Asians and
Hispanics are better treated regarding data. He
notes that American Indians and Alaska Natives
make up only 2% of the total US population.
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Snipp proceeds to consider privacy issues and
mentions blood samples in a case from Arizona
where data was widely shared. There are issues of
scale, the Chapter Houses of the Navaho being too
small to be considered by the Census Bureau, He
talks about the use of mobile phones and suggests
that they might make things easier in data collection
by indigenous groups. He concludes with several
points including that Indian groups themselves
define their membership and who has access to the
data collected.
Ian Pool then writes about the pre and post colonial
experience for indigenous peoples and notes the
entry of ‘big data’ to this situation. He offers the
following definition, ‘Data sovereignty (Dsov) is a
somewhat narrow twenty first century concept from
commercial law relating to the protection of
digitalised individual, governmental and corporate
information, and also to the safeguarding of the
national security apparatus from nefarious actions.’
Pool, in an article that covers a fairly wide field talks
about ‘parastatal’ corporations like the East India
Company in its day in terms of what he calls Data
suzereignty, D Suz, and compared to Data
sovereignty, D Sov. This distinction is useful and it
is worth thinking about these parastatal
corporations and Big Tech.
Pool talks about external data systems. He walks the
reader through a consideration of colonialism and
talks about the way settler states demonised
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indigenous groups and subverted their datasets.
Pool argues that what was left such as songs and
dances ‘constitute a form of memory bank for data’.
He then provides ‘a backstory’ to show the kinds of
effects involved which include ‘methodological
chasms between indigenous peoples and the wider
populations surrounding them’.
In a fairly wide ranging discussion involving cultural
capital, the degradation of the native, Tabloidism
and the prioritisation of certain statistics like those
relating to morbidity inter alia Pool goes on to
internal colonialism. He suggests that people might
lose data sovereignty when their credit card details
are held offshore. He mentions data hoovering and
talks about classification. Pool finishes by saying ‘It
would be tragic if this metamorphosed instead into
neo-D suz under transnational corporate rule
beyond the control of indigenous peoples or the
polity in which they live.’
Maggie Walker then talks about the five ‘D’s, of
indigenous Australian data- disparity, deprivation,
disadvantage dysfunction and difference. Then
there is the idea of ‘deficit data-problematic people’
and statistically informed pejorative stereotypes.
Walker talks about a ‘recognition space’. Maggie
Walter asks about the reality of numbers and their
deployment and their service throughout her paper.
Then it’s a matter of ‘Closing the Gap’, a pervasive
sense of data inequality for a group, a weighting of
ethnicity. Is this a closing of the gap between one
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sense of group and another? In the way nation
states collect data this is sometimes about scale
regarding the small size of dispersed populations.
Walter talks about ‘the trope of the statistical
Indigene’ outside of which there is, she argues, a
data desert’.
But the 5Ds add up to a frame which structures race
rand other relations. And provide a ‘virtual veil’ over
the situation of indigenous peoples. The frame
allows a new racism. Walter comes to say,
‘The advent of big data with its tendency to further
distance lived social and cultural realities from their
database embodiment, has only exacerbated the
pejorative power of numbers to further marginalise
and dispossess.’
Walter asks how the paradigm of indigenous
statistics might be disrupted and disturbed. Later in
a discussion relating to Larrakia sovereigny Walter
also discusses how to disrupt established tropes
regarding indigenous identities. As she concludes
Walter talks about a world view of those who shape
how indigenous statistics are ‘done’ referring to
Bourdieu’s 1984 idea of ‘synthetic unity’ she does
so. Finally Walter argues for ‘Indigenous framed
numbers’.
Francis Morphy then talks about demography and
argues that local understandings are important and
talks about ‘naming’ the indicators of indigenous
realities and prioritising those indicators. Morphy
talks about ‘enforced commeasurability’ and how
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numbers are use against indigenous people. She
talks about ‘the ontology of the quantifiable’ and
gives examples of data being used in a negative way
for indigenous people. Morphy talks about two
major aspects of data sovereignty. ‘It is not just sa
matter of contesting decisions based on indicators
preordained by others; it also involves the assertion
of sovereignty over the choice ODF indicators’.
Morphy argues for indigenous peoples to have
‘epistemological sovereignty over the data that
define them’. There is data and the way it is
aggregated. The way indigenous people are
compared and ranked shows the ‘enforced
commensurability’ that they live under. Referring to
Davis et al (2012) Morphy talks about how
indicators implicitly evaluate. There is an
interesting and possibly important discussion of
place which Morphy considers critical for
indigenous peoples.
Morphy talks about the ways in which indigenous
demography emphasises ‘substantive differences
that need to be acknowledged and accepted by
settler states if they are to formulate policy that
supports rather than undermines the self defined
goals of encapsulated indigenous peoples.’ Morphy
closes with a consideration of polygyny.
Diane Smith then asks who is the self in ‘self-
determine-nation;? Smith argues for ‘culture smart’
information’. Referring first to a quote from Einstein
‘(according to the available data)’ worth considering,
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‘Not everything that can be counted counts. And not
everything that counts can be counted’.
Smith looks to the ‘internal expertise and
institutions’ required by indigenous groups
regarding data along with access to data that is
culturally relevant and accurate, She lists a series
of questions that might yield the collective will of a
nation, clan, group or community’ in such a way as
to ‘mobilise sustained, organised action’. Smith is
talking about the governance of data and the abuse
that occurs from ethnocentric criteria and
definitions, about the way a ‘nullus fiction’ of
indigenous life occurs to leave it ‘empty, invisible
and unknowable’. At the same time there are
challenges to indigenous data governance. There is
a need now to ensure ‘resilient governance capable
of delivering outcomes’.
Diane Smith then provides a useful model with
several dimensions requiring data and information.
She asks where to start in matters of data
sovereignty and asks searching questions as to the
‘self’ involved, the appropriate demography and
governance performance. Smith talks of a ‘virtuous’
(her inverted commas) cycle of relevance and goes
on in a section entitled ‘Culture-smart information’
to speak of a ‘tyranny of the measurable’ which does
not meet the ‘complex knowledge economy’ found in
indigenous society, She sees ‘culture-smart’ data as
‘fundamental ingredients in the practical exercise of
sovereignty’. In her conclusion Smith goes on to say,
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‘Sovereignty includes being able to design rules for
the restriction and opening of data’.
Ceal Tournier then describes a way of certification
from an indigenous perspective. He speaks of a shift
after 1994 in ‘data and information sovereignty’. To
Tournier ‘the problems with the use of First Nations’
information stem from who is in control- and thus
what gets done, how it is done and who knows about
it’. Ceal Tournier, as Chair of the First Nations
Indigenous Governance Centre (FNIGC), said at an
earlier point, ’he who controls the data controls the
gold ‘(Tournier 2002).
Tournier goes on to say, First Nations’ citizens and
leaders acknowledge and act on the premise that
information needs defending and protecting; just as
we protect our lands, our forests, our animals and
our fish, we need to protect our data which are an
extremely valuable renewable resource’.
Tournier then gives examples of poor research by
outsiders involving data.
Tournier proceeds to talk about a red standard
(Tournier’s italics) emphasising First Nations
control of First Nations’ data and provides and
important history of the experience in Canada
involving Ownership, Control, Access and
Possession. Tournier points out that those
responsible must be versed in Juristiction, Policies
and Procedures and Repatriation. He suggests that
while these apply to Canada they may, with
modification, be applied worldwide by indigenous
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peoples worldwide. He closes by saying, ‘By building
information governance capacity, enacting our own
laws, entering into data-sharing and license-to-use
contracts, creating regional data centres and
repatriating our data First Nations are getting closer
to exercising full jurisdiction over our information’.
Then Hudson, Farrar and McLean talk about the
Whakatohea and ask for equality of access to data
and a datascape where rights to culturally sensitive
data be worked out fairly for iwi. The example given
first is the Whakatohea Maori Trust Board as ‘the
steward for a range of administrative datasets,
health and social service records, commercial
information, historical accounts, indigenous
knowledge, strategy documents and research’. They
talk of co-governance, this happening in the post
settlement period. The Whai Rawa superannuation
scheme of Ngai Tahu and the business incubator
model of Waikato-Tainui are given as development
examples in the post settlement period. The scale of
the Maori economy is examined as well as the
growth of Maori intellectual capital. They note that,
‘Through the increasing range of co-governance and
co-management relationships tribes are asserting
the importance of including indigenous knowledge
as an information source in environmental decision-
making.
Regarding iwi and data Hudson, Farrar and McLean
suggest,’Using a health analogy it could be said that
iwi suffer from inequities in data access and
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inequalities in data infrastructure’.They then go on
to talk of the ‘five safes’ framework used in the
Integrated Data Structure (IDI), a ‘linked
longitudinal dataset’. These include safe people, safe
projects, safe settings, safe data and safe output.
Referring back to the New Zealand Data Futures
Forum of 2015 they give four principles that include
Value, Inclusion, Trust and Control. In a useful
discussion of tissues and genome data they refer to
the Ngati Porou Hauora agreement with the
University of Otago on the genetics of Gout and
other matters. The discussion proceeds to the
Mataatua Declaration on the Cultural and
intellectual Rights of Indigenous Peoples of 1997 as
reinforced by the United Nations Declaration on the
Rights of Indigenous Peoples (UNDRIP).There is then
a discussion of research ethics informed by their
earlier points. This is followed by a review of
resource rights and interests and the use of the
Waitangi Tribunal in settlements which as lead to
the creation of pan-tribal entities such as Te Ohu
Kai Moana or the Crown Forestry Rental Trust..
The Whakatohea Maori Trust Board is then used as
a model for the use of data by an iwi such as the
creation of critical data archives. Hudson, Farrar
and McLean go on to say,’ Whakatohea consider
that access to government collected data and
information is a treaty right and that the tribal entity
is better placed to create benefit for tribal members
than government departments or research
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organisations’. They then provide a model with
exclusive rights, shared rights and shared interests.
James Hudson then talks about the Maori Plan in
Tamaki Makau Rau, Auckland, He suggests that ,
‘The Maori Plan clearly articulates a Maori vision for
Tamaki Makaurau and is a touchstone for ongoing
dialogue about Maori-specific data to support that
vision’.Regarding the Treaty of Waitangi and local
government Hudson talks of partnership, active
protection and redress. He then talks about a duty
to consult. Following a discussion of governance and
operational matters to do with the Independent
Maori Statutory Board Hudson considers the Maori
Plan. He says, ‘While some data were available about
Maori, few, if any, were available that could be
viewed as useful for Maori’ (Hudson’s italics) and
proceeds to discuss a framework for monitoring and
measuring Maori outcomes in Tamaki Makau Rau.
The Maori Plan is to follow tikanga, last for thirty
years and address a broad range of issues. Hudson
mentions the difficulty in sorting out national from
local data especially in environmental and cultural
factors. He considers the establishment of a Data
Strategy Expert Panel and notes an emphasis on
‘safety’ (Hudson’s inverted commas) around tikanga
Maori and ‘technical robustness’.
Rawiri Jansen then talks about an indigenous
professional class in Aotearoa New Zealand and
shows how data can be mobilised to inform action
by Maori. He does this through case studies showing
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‘how data can be used to inform interventions that
the NHC leads to deliver improved health outcomes
for Maori’.Going back to Nopera Pana-kareao he
suggests that ‘Data governance requires thought
about both the substance and the shadow of the
data’. He talks of health rights and the need to
‘deconstruct institutionalised racism’. Taking
rheumatic fever and the Mana Kidz programme as
examples Jansen points to the value of linked data
in providing a ‘rich picture’. Then he talks of housing
plans and ‘housing literacy’ and the construction of
a dataset to better manage rheumatic fever. He
describes the use of an AWHI scorecard to follow
developments. Jansen goes on to discuss
cardiovascular disease and use of Mohio Forms
available on the internet to monitor data and provide
a ‘rich data picture’ which helps in measuring equity
performance.
Jansen talks about sharing data and mentions the
Metro Auckland Data Stewardship Group (MADSG)
‘to navigate the issues of health information use,
management and privacy across the health system’.
He talks about the idea of a Maori ‘data-sharing
governance framework’ which would be ‘an
indigenous data sovereignty framework’. He
concludes by saying, ‘It seems that we move up a
hierarchy from data visibility and data accessibility
to data sharing and data control’. Jansen‘s final
sentence is ‘Maori sovereignty is informed by Maori
data sovereignty’.
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Ray Lovett then talks about the need for
professionally trained indigenous statisticians in
the Aboriginal and Torres Islander community. He
says the ‘need to reflect reality is what Walter and
Anderson (2013) refer to as ‘the cultural framework
of Indigenous statistics’. Lovett talks of local distrust
in data research and then the need for Indigenous
statistical capacity. He points to suggestions that
the reliability of Aboriginal and Torres Strait
Islander data has been negatively affected by ’the
purpose of the data collection, who is conducting it
and the mode of collection’. As well as issues of
capacity there are matters to do with the
chairmanship of committees and groups that ‘advise
‘(Lovett’s inverted commas) and not direct. He goes
on to say that while ‘the gap’ (Lovett’s inverted
commas) is not closing, important cultural
strengths are not noted. He asks, ‘What of the distal
indicator of a strong connection to mob and country
showing a positive correlation with reductions in
cardioivascular disease outcomes? (Rowley et
al.2008)’ and goes on to talk about indigenous
conceptions of well being and the value of
Indigenous culture. Lovett discusses the teaching
and learning of mathematics which us critical in
developing statistical capacity and laments the
financial costs of higher education. He mentions a
programme called Mayi Kuwayu and the
development of statistical capacity in longitudinal
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studies and concludes by emphasising the need to
build statistical capacity.
Yap and Yu then talk about indigenous data
sovereignty in the case of the Yawuru. A Yawuru
language revitalisation program is included in the
discussion. They begin by addressing the flaws they
see in the ‘Closing the Gaps’ policies. This is not all
about adopting the ways of the majority. They refer
to Taylor’s 2008 suggestion of a ‘recognition space’
and then to Kukutai and Taylor’s 2013 insights into
how data might be indigenised. They argue for the
development of ‘indicators that are culturally
appropriate and reflect indigenous world views’.
They call for ‘information on cultural dimensions,
indigenous ecological values and indigenous
peoples’ unique relationship to nature and the living
landscape.’
Yap and Yu ask ‘how does one begin to
operationalise the recognition space so that the
information reflects Indigenous aspirations and
world views while simultaneously informing
government planning and reporting needs?’ They
refer to five recognition principles developed by
Kukutai and Walter 2015. These are geographical
diversity, cultural diversity, other ways of knowing,
mutual capability building and indigenous decision-
making.
Yap and Yu proceed to an analysis of Aboriginal and
Torres Straits Islanders beginning with the Native
Title Act of 1993 which provided a legal framework
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for a self determination agenda. They suggest ‘The
Native title process provided a platform for the
process of knowledge building and capacity building
among Yawuru.’ They then describe the Yawuru
Knowledge and Wellbeing Project which involves
mapping and other features. The case studies
described deserve to be considered in detail and a
thorough reading of their work is recommended. The
study seems highly appropriate as, to use the words
of the authors, ‘the reality of native title sets in’.
Desi Rogriguez-Lonebear gives examples from the
USA regarding data identity and tribal membership.
He points out that in the ‘data mecca of the United
States American Indian tribes face a paucity of data
about their own populations.’ He explores ‘the
nascent data revolution now getting underway in
Indian country as some tribes regain data
sovereignty’ and considers ‘how tribal data
sovereignty can be a powerful tool in decolonisation
and in pursuit of tribal developmental goals.’
Rodriguez-Lonebear notes that ‘For indigenous
peoples data were everywhere and survival was
often tied to one’s ability to gather, analyse and
share this knowledge’. He also notes the importance
of oral history before considering how data
sovereignty became data dependence with a
recounting of what happened in a museum context
with the brain of an elder.
Roderiguez-Lonebear argues ‘Indigenous data
engagement in the United States is inextricably tied
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to the subjugation of American Indians and federal
policies of Indian extermination and assimilation.’
He talks about the omission of the majority of
American Indians from the census for a very long
time because they fell under the ‘Indians not taxed’
category. He suggests that ‘Indigenous data
transitioned from a means of survival to a
mechanism of federal administration’. He argues,
‘The data collection activities of tribes now largely
revolve around mandatory federal grant recording
and many tribes employ grant officers or
administrators to oversee these efforts.’ He draws a
distinction between New Zealand and the USA and
points to the difficulty tribes face in gathering data
about themselves. This makes policy making
difficult.
Rodriguez-Lonebear goes on to argue that this is
why often the data tribes themselves present is
regarded as inferior to that collected by the state
governments such as that of Montana. He talks of
tribal youth being the ‘data warriors’ needed to steer
a data revolution. He raises the question as to who
should be conducting censuses, the tribes or the US
government. He notes the difficulty in maintaining
sovereignty in a dependent situation and suggests
that data sovereignty is critical. He also notes debate
on the idea of blood quantum and the need to have
good data on tribal membership. He suggests in
conclusion that the silo mentality must be dropped
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and that cooperation is necessary for data
sovereignty.
Paul Jelfs then discusses the Australian Bureau of
Statistics in terms of indigenous governance in the
case of Aboriginal and Torres Strait Islands. Jelfs
gives a strong paper on the role of the ABS in this
area talking about such initiatives as the Indigenous
Community Engagement Strategy, the Roundtable
on Aboriginal and Torres Strait Islander Statistics
and other things such as Census Story Books. He
concludes with a model for ‘solution-centred and
collection-centred statistics’.
Finally Darin Bishop talks about the Maori
Statistics Framework and the conceptualisation of
Maori indicators. He mentions systems found
around the world regarding statistics of indigenous
peoples. Bishop suggests that ’New Zealand has
gone further than any other nation-state in seeking
to develop such systems and to accommodate the
needs of the indigenous people. Notwithstanding
this, significant deficiencies remain and these
undermine Maori data sovereignty.’ Bishop provides
a model of the measurement process and also a
critique and the need for dis-aggregation of data and
to follow recommendations from the United Nations
Permanent Forum on Indigenous Issues.
He talks about the shift away from ‘closing the gaps’
to a focus on Maori potential. Bishop speaks of the
need to provide Te Puni Kokiri, the Ministry of Maori
Development established under the Ministry of
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Maori Development Act of 1991, with ‘relevant and
reliable evidence’. Bishop notes the small window of
opportunity for Maori to act on data and proceeds to
offer a set of suggestions for users and potential
users of Maori statistics. He mentions Te Kupenga
of 2013 a survey of Maori wellbeing following a
census. He talks about limitations on data
pertaining to whanaungatanga.
There is also a discussion of an emphasis on the
individual as distinct from notions of the collective
when it comes to ethnicity. Bishop proceeds to list a
series of challenges ranging from Maori migration
patterns regarding New Zealand and Australia, to
cultural outcomes and various other important
areas and argues for the voice of Te Mana Raraunga,
the Maori Data Sovereignty Network. In conclusion
Bishop goes back twenty years to look at the
development of a Maori statistics framework and
reviews progress along with deficiencies that
remain. At the close of an excellent discussion he
mentions the scope for building the statistical
capability of Maori communities and organisations
amongst other things.
Going to the voice of Te Mana Rarauna the Maori
Data Sovereignty Network the following points are
made:
1. asserting Maori rights and interests in
relation to data
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 23
2. ensuring data for and about Maori can be
safeguarded and protected
3. requiring the quality and integrity of Maori
data and their collection
4. advocating for Maori involvement in the
governance of data repositories
5. supporting the development of Maori data
infrastructure and security systems
6. supporting the development of sustainable
Maori digital businesses and innovations
Conclusion
We have a collection of some note in Indigenous Data
Sovereignty. Kukutai and Taylor conclude their
excellent introduction by referring to UNDRIP as
they have throughout. They note the distinction
between ’sovereignty as it relates to digital spaces
and the forms of data stored in those spaces’.
Differences in the CANZUS states are noted. The
United States Indigenous Data Sovereignty Network
and its four focus areas of data for sovereignty, data
collection and access, data storage and security and
data as intellectual property are pointed out.
Kukutai and Taylor stress the emphasis that state
agencies have placed on ‘populations’ rather than
‘peoples’. They point out that they have provided a
voice for informed people about indigenous
sovereignty. They ask, again with reference to
UNDRIP, for ‘a relocation of authority over relevant
Te Kaharoa, vol. 14, 2021, ISSN 1178-603524 Maramara me te Iwi Taketake
information from nation states back to indigenous
peoples’.
Comment
In describing a displacement of the situation
whereby the Indigenous entity controls data to one
where the nation state controls the data Kukutai
and Taylor and most of the contributors to this
volume do not fully round on the role of ‘Big Tech’.
In the introduction Kukutai and Taylor do
summarise Ian Pool’s argument and talk about the
irony Pool finds when just as the indigenous peoples
are coming to terms with the data that the Nation-
states have of them ‘Big Data’ is emerging to engage
in and in some ways own the data of the Nation-
states. This, by the present writer’s extension, and
not necessarily with reference to Kukutai, Taylor or
Pool, might mean a progression and a replication
whereby the nation states get left in the position that
they had created for indigenous minorities or
something like. As the Nation-states in relation to
Big Tech or what the present writer calls the
‘algorithmic state’ (Cleave 2020, 2021) begin to look
like the Indigenous groups in Canada, the US,
Australia, New Zealand and elsewhere in relation to
those Nation-states. The Nation -states, especially
the smaller ones, are like stars that are fading, at
least for the moment, while the stars of Big Tech are
waxing.
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 25
Another way to put this is that in making the
comparison we might be moving from one ‘uncanny
valley’ to another one just as ‘creepy’ to borrow
terms from Sara Watson (2014) in her discussion of
what she calls ‘data doppelgangers’. Watson gives a
background to her terms,
‘Since the 1970s, theorists have used the term
"uncanny valley" to describe the unsettling feeling
some technology gives us. Japanese roboticist
Masahiro Mori first suggested that we are willing to
tolerate robots mimicking human behaviors and
physical characteristics only up to a point: When a
robot looks human but still clearly isn’t.
The threshold is where we shift from judging a robot
as a robot and instead hold it against human
standards. Researchers at the University of Bolton
in the UK have described this shift as the "Uncanny
Wall" in the field of digital animation where
increasing realism and technological advancements
alter our expectations of how life-like technologies
should be. I would argue that we hit that wall when
we can't distinguish whether something is broadly
or very personally targeted to us. The promise of Big
Data has built up our expectations for precise
messaging, yet much of advertising is nowhere near
refined. So we don't know how to judge what we are
seeing because we don't know what standard to hold
it against.’ (Watson, 2014).
Sarah Watson’s expression ‘data doppelgangers’
refers to the situation where a false sense of the
Te Kaharoa, vol. 14, 2021, ISSN 1178-603526 Maramara me te Iwi Taketake
individual is created, one that the individual has no
control over the shape or shaping involved. The
same might be said of the Indigenous group as
represented in the data collection of the Nation-
state. To return to Pool’s point, the emerging role of
Big Data takes this to a further remove in that the
representation of Nation states themselves as well
as the ethic groups within them, Indigenous and
otherwise, come, in a collective rather than an
individual way, to make up a set of data
doppelgangers. Considering Watson’s argument,
what then the relation of the indigenous entity to Big
Tech or what the present writer calls ‘the algorithmic
state’? And what if, referring back to Maggie Walter’s
points about data deprivation above, in the absence
of a positive relationship between Big Tech and
Indigenous groups the latter simply stay in data
deserts? What if, instead of uncanny walls or valleys
there is an eerie silence upon a plain. What if ethnic
groups are simply left off the map as the hunting,
gathering and farming of data proceeds? What if,
when we look at such a high and low tech contrast
we are looking at a version of the Hot and Cold
societies described by Levi Strauss between history
based and myth based societies (Levi Strauss
1966)? And if we closely looked at this would we see
that while some may be data poor they might be rich
in myth, wealthy in an idea of themselves that
makes sense to the group and offers emotional and
psychological support?
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 27
There is a general question that might apply. Is the
machine learning found in Big Tech set to use
algorithms to know you as a citizen or to know you
as a consumer? To turn on this point, as the Nation-
state to the Indigenous group is replicated in the
relation of Big Tech to the Nation-state the nature of
the knowledge involved changes. No longer are we
talking about data and rights and obligations of a
civic kind, at least not necessarily. In its most vulgar
form the data context of Big Tech and the individual
member of a Nation-state or an Indigenous group is
basically a market context. A market economy
without reference, say, to a political economy or, for
that matter, to a political identity.
Whose data context, whose economy is this?
Now the nation state is being displaced in certain
respects by the algorithmic state or at least the
present writer suggests so (Cleave 2020 One- Four,
2021 Five-Eight). This especially relates to data. ‘In
data we trust’, says an Amazon executive (Cleave
One op cit). But, again, who owns the algorithmic
state and how is it directed? The first part of this
question is, at least at first glance, easily answered.
Amazon, Alibaba and the like and their shareholders
own Big Tech. Coming to the second question, as to
how all of this is directed, we come to machine
learning. Again the reference here might be to The
Algorithmic State History and Theory (Cleave, Five op
cit.) and the idea that it began with Bayes. The point
might be that this is a direction by algorithm and
Te Kaharoa, vol. 14, 2021, ISSN 1178-603528 Maramara me te Iwi Taketake
machine learning for a great if not the most part and
this might be new in human history even though the
historical precedents stretch back to the publication
of Bayes’ work (Bayes 1763).
To consider the above propositions several
examples, albeit from the silly side of the sanity
ledger might be considered. The media in Myanmar
is dominated by Facebook which will not allow
commentary by the government, said government
being the military. San Salvador is considering
allowing and encouraging Bitcoin as a valid
currency in the context of a weak local currency. In
2021 there has been the example of Twitter and
other platforms banning the President of the United
States from commentary. In these examples
cardinal principles of state may be seen
compromised, communications in the Myanmar
case, economy in the San Salvador example and
politics in the case of Trump as President of the
United States of America. At the same time Big Tech
is looking strong against competing interests in the
fields concerned, media, economics and politics.
If we were to find a collapsed or failed nation state
that allowed Facebook and Bitcoin which also gave
free rein to Twitter and the like we might be looking
at a displacement of some significance.
Throw in neighbourhood meshes and the like...
It might be worth pointing out that in Aotearoa-New
Zealand of the early 2000s this is the time of ‘He
Puapua’. This is an attempt by Willie Jackson and
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other Maori MPs to provide more say in government
departments for Maori. But what is the value of
having more say in areas where data ownership and
control might be decreasing? Is the effort to create
‘He Puapua’ a chasing of shadows, phantoms of
power? If data control is increasingly in the hands
of Big Tech are we better to ask the relation between
Indigenous groups and Big Tech than that between
Indigenous groups and Nation states? We might
consider the review of Kukutai and Taylor above in
these terms.
Will Nation states rein in Big Tech and attempt to
remain or become again the key players in data
sovereignty? There is a serious situation here for
Indigenous groups. If Indigenous groups are trying
to gain control of data, to find again their
sovereignty of data in the wrong place then there is
a twist again to colonialism. This is a sovereignty
game of some portent in that the Kukutai and Taylor
collection shows the kind of energy going in to claim
a resource that may not be there in the Nation-state,
a resource that has shifted in the time of the data
claiming process, over the last quarter century, say.
Is there a grip that the indigenous society might
secure on the algorithmic state on ‘Big Tech’, a hold
like UNDRIP might have given indigenous interests
over the nation state?
What is the significance of the data shift, the shift
from state to parastatal or what the present writer
has called the algorithmic state or, more simply, the
Te Kaharoa, vol. 14, 2021, ISSN 1178-603530 Maramara me te Iwi Taketake
shift to Big Tech as the critical owners of data?
Given the points about identity and sovereignty
above the shift is considerable. There is a shift in
shapes, political, epistemological and other as well
as a shaping of ethnicity and nationalism.
Is this some kind of migration from one data zone to
another, one holding pen of information to another?
Is this, at base, all about data as clicks? Every
movement of the mouse and every dwelling upon or
return to a page or a link is in the zone of Big Tech
rather than in the data zone of the nation state. And
each click is a point in the data bank, the holding
pen of data of, say Google or another Big Tech
operator.
There is a mix and sometimes a contrast between
skills and sentiment in the Kukutai and Taylor
collection as there is in a lot of the commentary
about data. The ‘skills’ relate to the algorithms
involved, the efficiency and the effectiveness of the
data collection involved, the skills in the hunting,
fathering and farming of data. The sentiment often
relates to the Nation-state or, throughout this
collection, the Indigenous group involved, to the
critical identity point upon which to hang data.
There are also issues of scale, the Indigenous groups
generally being too small to allow effective, cost
effective data collection. As mentioned above
Morphy states very well the problems of small scale
data collection for Indigenous groups. But the same
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 31
logic might apply for the small nation state like New
Zealand.
With the situation of the very small nation state and
the bigness of Big Tech to consider there is also a
strangeness of place, such places as New Zealand
being easily seen and identified by virtue of their
isolation from continental Europe or America. At the
same time there is a placelessness of Big Tech, the
latter existing in several spaces including
cyberspace without being defined by the bounds of
the Nation-state.
With all of this there is also, as introduced above
with the consideration of sentiment, what might be
called a constellation of comfort, a cluster of
sentiments. This comfort constellation, this
sentimental structuring of sovereignty is seen
throughout the Kukutai and Tatlor collection with,
say, Pool’s curation of the New Zealand context. The
cultural and political loading in Pool’s argument
functions as a kind of algorithm following Cathy
O’Neill’s use of the term (O’Neill 2018). O’Neill uses
the example of a recipe as a kind of algorithm. Pool
takes a pinch of Salmon, a dash of Belich and a mix
of positions including a spray on Moon and a
thumbs up to Biggs to provide a picture against
which or within which data might be considered.
The cold reality of data collection meets the soft,
feel-good sentiment of a slightly dislocated
nationalism, a set of intellectual conceits, an
emotional fall back position, a strange nationalism.
Te Kaharoa, vol. 14, 2021, ISSN 1178-603532 Maramara me te Iwi Taketake
Several commentators imply that what the
Indigenous group want, their ambitions in terms of
their current circumstances, is the appropriate
measuring stick for analysis.
These intellectual circumstances, this comfort
constellation, underpin ethnicity as they do
nationalism. It is correct to talk about the
epistemology of sovereignty, as some commentators
do in the Kukutai and Taylor collection. To be
forever put up against foreign measuring sticks
outside one’s culture is distressing. Such might be
seen more clearly in cases of the most dispossessed
and this is one of the many values in this collection
of papers as they add up to a kind of classic, if
extreme, statement of estranged knowledge
arrangements, of grievous and sometimes absurd
knowledge conditions.
The critical link might now be between the
Indigenous group and Big Tech. This might give us
in the Maori context Ngai Tahu and Amazon,
Rangitane and Alibaba or any kind of combination
of iwi or pan iwi groups and Big Tech operators.
Such is not considered by the commentators in the
collection at least not in any depth. But with respect
to data, especially data of buying and selling habits
Big Tech has the data market, if such it be called,
covered as it uses its algorithms to analyse that
data. Iwi may well feel the need to be a critical part
of such mixes of data and power.
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 33
Elsewhere (Cleave Two Suns? Five 2021) the present
writer has argued that this is a matter of space in
that if we consider, for example four types of space,
neighbourhood space, national space, outer space
and cyberspace we might see that Big Tech owns
data in cyberspace and with the neighbourhood
mesh Amazon owns data in the local space while
Nation-states might own data in the space of the
nation. The outer space situation is mixed with Big
Tech now operating with its own data there.
Somewhere in all of this are the ethnic groups, the
minorities including Indigenous groups. A
beginning point for analysis might be to consider
where Indigenous groups stand in these four
spaces.
The problem might be that the spatial template
along with political, cultural and other templates
commentators in the Kukutai and Taylor collection
work off is that of the Nation-state which may or
may nor be treating the Indigenous group fairly. But
that template, it is argued here and elsewhere, is
suspect. We might come back to Ngai Tahu or
another iwi comparing its data with that held by
Amazon rather than or, at least, alongside the data
held on that iwi by the New Zealand government or
any other government for that matter. Amazon
might hold as much or more data than the New
Zealand Government but it might be data more
attuned to the market world that the New Zealand
Te Kaharoa, vol. 14, 2021, ISSN 1178-603534 Maramara me te Iwi Taketake
citizen lives in. And so the data picture of all groups
including the Indigenous population in New Zealand
held by the New Zealand state is one version while
the data held of members of these group in Big Tech
data banks might be another picture altogether. It’s
a question of assumed authority, of, if you like,
colonialism and the mentality involved, of
dependency, the nation state is assumed to have a
better, a truer pictur
We are looking at system of hunting and gathering
data. A search engine hunts for data which is
gathered and hunted again as more data is searched
and found. Crunched, and then farmed. This system
works in terms of machine learning which dates, as
mentioned above from Bayes. As mentioned above,
the present writer has described this in a paper
subtitled The Algorithmic State, History and Theory
(Cleave 2021). Not addressed there but considered
here is the blunt question, who is in charge?
Here is where it might get tricky for several kinds of
scholars including those interested in ethnic affairs.
One thing not to be assumed is that the Nation-
states, especially the smaller nation states like, say,
New Zealand, have effective control of data. To look
at the situation of New Zealand Maori and data and
to posit a strict control of data relating to Maori by
the New Zealand state is not helpful when data to
do with purchases, key movements on computers
and, in fact, a multiplicity of data collection
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 35
processes is outside the purview of the state and
effectively in the hands of Big Tech.
Then there is another matter to do with the last
phrase, ‘the hands of big tech’ as this phrase
assumes a personality behind it all. We have moved
beyond state authority over data and then to a point
beyond personal power. We may have talked about
Bezos aka Amazon for a while, we may continue to
do this even when Bezos removes himself
progressively from day to day operations at Amazon
as he is doing. But eventually we might have to
consider that Amazon is a system removed from a
charismatic personality, the most effective system
we have perhaps of hunting, gathering and farming
data. We thought there was a super brain a
charismatic figure at the top but it was always to do
with the algorithm known and developed in machine
learning.
We might then proceed from these impersonal
systems of data collection, analysis and use to ideas
of political economy. Such ideas might relate to the
arguments in the collection of writings about
Indigenous data sovereignty by Kukutai and Taylor.
However, matters of state and ethnicity are lost in
the hunting, gathering and farming mix where the
objective is to build better and better learning
systems as the machine learning is set to do. The
search engines do not have ethnic or national flags
as those things have been known. The data is
gathered and put together to create a world with its
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own characteristics, its own map, and its own
political economy. In that world it can be seen what
sells where, who buys what, how often, in what
quantity and a set of data aggregates, of data
identities is created. This is more than a
doppelganger, a version of the real world, it is its
own thing. Forms, shapes of state and ethnicity are
not, or at least not necessarily found in the way that
they once were.
The use of data in the context of machine learning
begs questions about identity and authority. We
come back again to the question, ‘who is in charge?’
The key point of view, if there is one, is unclear. Data
is sorted, links are made, data is sought related to
those links and a learning model is set up relating
to individual and group. Again it is a matter of
hunting, gathering and farming data. But who or
what runs the hunt, the gathering process and the
farm?
There are some serious aspects to all this. The pain
in stripping or absenting data about themselves
from people is immense and in some respects the
Indigenous data situation is indicative of the wider
population now in their relation to Big Tech, a shape
without a face that owns the data about people
without their say. Regarding this immense pain
which is reflected in each part of the Kukutai and
Taylor collection as it is in the work of O’Neill and
others regarding the wider population, we could talk
about a psychic epidemic, of mental illness in the
Te Kaharoa, vol. 14, 2021, ISSN 1178-6035Maramara me te Iwi Taketake 37
form of mass psychosis. We could ask how we might
step out of our minds to assess this situation. We
could see a population of ourselves as weak and
vulnerable persons in state of panic and lost in a
childlike trust in the Nation state. We could consider
all this as a pathological way of seeing reality.
We could talk about about powerless masses and a
god-like few of powerful individuals who front the
technology. We could talk of the addictive aspects of
that technology. Of menticide. Over time we could
talk of inter-generational trauma or of totalitarian
psychosis which we had formerly reserved for
fascism.
Or, to put it straight, can we handle data? If so,
how?
We could come directly to questions of management.
Is New Zealand of sufficient scale and capacity when
it comes to data that it can effectively meet the very
real and extremely important needs of the Maori?
How many nation states have the scale and capacity
to represent the data of Indigenous and minority
groups let alone majority groups?
We are now looking at data and behaviour in a way
not hitherto possible. Data is not simply a matter of
record it is a resource for prediction. So we have
data on what people buy and what they might buy,
how that might be suggested. Going forward from
that requires statistics from Nation-states like
births and deaths to supplement data on clicks and
searches neighbourhood meshes and other data
Te Kaharoa, vol. 14, 2021, ISSN 1178-603538 Maramara me te Iwi Taketake
that has been hunted, gathered and farmed by Big
Tech. However the latter might provide the bulk of
the data involved.
We might talk, as the present writer does, about The
Data of Nations (Cleave, Four 2020). And the phrase,
‘the data of nations’, might have several meanings.
One could be that nations own data. Another
implication might be that data transcends nations
and redefines them. The phrase could refer to Adam
Smith’s expression, ‘The Wealth of Nations’ or it
could be implied that the data of nations is yet
another resource of Big Tech. We might talk about a
chain effect where there is the data of nations, the
data held by Big Tech and the data of indigenous
groups Whether nations or Big Tech are at the head
of the chain might be debated. Kukutai and Taylor
start their collection with the correect asertion that
Indigenous groups did once and should again be at
the head of the chain regarding their own data.
Looking forward, what happens to data, how it is
used in the context of machine learning and
algorithms varies through the chain with Big Tech
having superiority in such a context for the most
part. Throughout such a chain we might think
about the expression, ‘data is power’.
We are looking at data and the construction of an
image. We could go back to Maggie Walker’s five ‘D’s
above, of indigenous Australian data- disparity,
deprivation, disadvantage dysfunction and
difference in the Kukutai and Taylor collection. And
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